Impact of Monetary Shocks on Stock Prices and Macroeconomic Variables: A Comparative Empirical Study on India and the USA
Authored and Presented
By
Shah Saeed Hassan Chowdhury
Department of Economics and Finance
MiddleTennesseeStateUniversity
May 15, 2008
Impact of Monetary Shocks on Stock Prices and Macroeconomic Variables: AComparative Empirical Study on India and the USA
I. Introduction
Although money is thought to be neutral in the long run, it affects the output in the short run. It is always interesting to know how the economy responds to the exogenous monetary policy shock. In the context of a developed country like the USA huge research has been conducted on this issue (Christiano et al. (1997) Christiano et al. (1998)). Even now the economists and academicians are trying to improve the econometric models to have a better knowledge about the monetary policy issues. However, over the years with various identification schemes there are some agreements as follows: after a contractionary monetary policy shock, short term interest rates rise, and aggregate output, employment, profits and various monetary aggregates fall and price level responds very slowly (Christiano et al. (1998)). On the other hand, few investigations have been done so far to trace the effect of monetary shocks on the macroeconomy of developing countries. India, a fast growing economy, is no exception in this regard. Reasons are probably the import-substitution policy adopted by Indiauntil 1980s and less autonomy of the central bank in the determination of exchange rate and monetary policy interference before early 1990s. Moreover, a longer data series is needed to come to a reasonable conclusion, which now India to some extent fulfills.
The price of a stock is the present value of all the future cash flows. The cash flows depend on firm-specific as well as market conditions. From the viewpoint of a portfolio manager the firm-specific risk can be diversified away in a big portfolio of many assets, but market risk cannot be eliminated. Market risk evolves from the macroeconomic condition of the country concerned or even the world economic and political conditions. Thus any monetary shock is supposed to impart some impact on the stock prices through the output channel. In the last two decades, the importance of the stock market of an emerging country like Indiahas increased many folds. The main reason is the low correlation between stock returns of emerging markets and that of developed markets. Portfolio managers have the opportunity to diversify the portfolio even more thoroughly, which makes the existing portfolio more efficient in terms of trade offs between expected return and risk.
In this paper an effort has been made to investigate how the monetary shock may be related to stock market in a high-performing emerging market like India. In case of an organized developed economy like the US and Japan stock price may even work as an indicator for the future growth of the economy (for example, Schwert (1989).Schwert (1990) points out that a change in discount rate may affect stock price and investment in the similar fashion, but the output appears with a delay. Moreover, stock price changes indicate wealth changes, which affect consumption and investment. For an emerging country like India, it can be assumed that stock market is not capable of predicting the future real activity of the economy. In this study, thus, I have assumed the stock price is the contemporaneous outcome of all the effects of the policy and macroeconomic variables.
Rapach (2001) examines the effects of money supply, aggregate spending and aggregate supply shocks on real US stock prices in a structural VAR (Vector Autoregression) framework. Findings show that macroeconomic shock affects stock prices and interest rate has a negative relation with real stock return. Lastrapes (1998) also uses VAR to find that expansionary money supply stocks raise real stock prices and lower interest in short run and money supply shocks explain one-third of the variation in real stock prices in the short run. Patelis (1997), Thorbecke (1997) and Neri (2004), among many others, have used VAR framework to study the relation between monetary policy and stock market. All find that stock returns respond negatively to a contractionary shock of monetary policy, but monetary policy shocks can only explain a small portion of stock return variation.
The objective of this paper is to examine the impact of monetary shocks (T-bill shocks in the absence of monthly data of policy instrument like Federal Fund Rate) on macroeconomic variables and stock prices of India and that of the USA. Then the impact can be analyzed from the viewpoint of developed and emerging market. As a corollary, the monetary impact on macroeconomic variables, both contemporaneous and lagged, are examined and compared. Macroeconomic variables are industrial production, money supply (M1), consumer price index, and 91-day T-bill rates (Federal Fund Rate for USA). All these variables are considered in a structural VAR framework. Appropriate restrictions are imposed to explore the likely contemporaneous and lagged relation between the variables.
Two types of identification schemes are used. In the first, restrictions are imposed such that stock price acts as the outcome of all the contemporaneous relation with other variables. In this setting, it is interesting to see how long the impact stays in the stock prices since an innovation occurs. In an efficient market, the stock price adjusts to the new information very quickly. For example, the market is full of analysts who should contribute enough to adjust the macroeconomic information in the stock prices. Violation of this means opportunity for abnormal profit for some investors. In the second set up, the stock price reacts to all the macroeconomic variables contemporaneously, but T-bill/fund rate is not influencing other variablesnow, rather T-bill/fund rate is reacting to the state of the economy. Consequently, the T-bill/fund rate influences the output, consumer price, commodity price and exchange rate next period. This is the identification scheme used in Christianno et al. (1998).
The structure of the paper is organized as follows. Following section discusses the very brief view of the changes that occurred in India since early 1990s. Section III gives details about the sources of data and the necessary transformation of the data. This section also provides how required restrictions are imposed for the examination. Section IV explains the empirical results. Concluding remarks are presented in section V.
II. Indian Economy and Capital Market since Early 1990s
In 1990, Indian economic policy fell to a serious balance of payment crisis, which led India to undertake a series of economic policy reforms. Economic reforms took place in foreign exchange management, industrial policies, fiscal policies, monetary policies and international trade policies. These reforms obviously allowed private sectors and markets to play stronger role in the allocation of resources.
In 1990s, India was one of the top 10 economies in the world in terms of average growth rate of GDP (Bhide, 2001). The higher growth rate was a source of risk due to more exposure to internal and external shocks. The sources of internal shock were various state subsidies, support to loosing government enterprises, etc. Some of the important external shocks are debt-servicing of foreign loans, exchange rate, etc. The main concern of India in the 1990s was to continue high growth and increase domestic income (in order to reduce fiscal deficit). Tax rate was reduced to achieve the target. The initiative to reduce external exposure started with the withdrawal of governmental intervention in foreign exchange rate determination. Thus RBI (Reserve Bank of India, the central bank of India) now only gives the indicative rates to the market and the actual exchange rate is determined by the market forces (Bhide, 2001). As a part of trade liberalization, tariff and non-tariff trade barriers were reduced by decreasing duties and import restrictions. There was also relaxation for the inflow of external capital. Capital markets had no price controls. Industrial policy changes permitted easy licensing, more foreign collaboration, import of machinery, and less beauracracy. Monetary policy also had abrupt change to cope with other changes. There was a big reform in the banking sector. Statutory reserves were reduced. The monetary authorities use open market operations to influence money supply to a greater extent using the improved market for government securities.
During2000-2005, market capitalization to GDP ratio went to 77 percent, which clearly reflects the trend in the foreign capital inflows and growth in the domestic investment base (Purfieldet al., 2006). Foreign investors held about 10 percent of GDP in equity assets. The domestic institutional investor base also expanded during the time. Insurance, pension and mutual funds’ assets amount to almost 15 percent of GDP, with significant portions in vested in equity (Purfield, 2007). The SENSEX increased at an annual compound rate of 17 percent during the period 2003-2005. The inflow of foreign capital was approximately $26 billion. This phenomenon was probably the outcome of low interest rate in the USA and growing attractiveness of Indian capital market. Market was relatively stable and Indiaeffectively shielded itself from situation like Asian financial crisis. The confidence of the investors can be illustrated by the Price-Earning ratio of more than 20 and that of technology firms of 30 (Purfeild, 2007).
There was approximately 31 percent growth in the initial public offering in 2006 alone. In a recent dramatic rise the BSE SENSEX jumped from 8,929 in 2006 to 14,724 in February 2007. Obviously it raised questions whether or not the price can be supported by the fundamentals of the economy.Over optimism sometimes grips the stock market, which is very harmful when eventually the bubble busts. A good example could be the economic turmoilMalaysia faced when the Asian financial crises broke out in the region. In this sense, this paper may also give some idea about how the stock prices react to the macroeconomic shocks. A weak relationship would mean the possible detachment of financial market from the economy and formation of bubble in the asset prices.
III. Data and Methodology
Monthly data for the period February 1993 through December 2006 have been used for India. Industrial production, consumer price index (CPI), money supply (M1), stock indexes, and exchange rates(Rupee to US dollar) are collected from International Financial Statistics (IFS) published by International Monetary Fund (IMF).[1] 91-day T-bill rates are collected from RBI.[2]The USdata covers from 1959:01 through 2007:09.Industrial production, money supply, stock price index, exchange rate, commodity price and CPI are used in log form. T-bill and fund rate are not in the log form. T-bill and fund rate are used as short term interest rate for India and US, respectively. Commodity price index is constructed from equally weighted food, beverage, agricultural raw material, metal, and oil price indices.[3]All the variables are set up in a VAR framework. I have used 14 lags for the US model. For India, the model has only 4 lags since it has a small dataset.[4]
In the first identification, I have used the setup used previously by Sims (1992). In this case, fund rate or T-bill affects other variables contemporaneously. So, stock priceis influenced byall other variables contemporaneously. The restrictions are shown in the following matrix format.
=+ … + +
Where FFR or TBL = Federal Fund Rate or 91-day T-bill rate, FEX = foreign exchange rate, CPI = Consumer Price Index, M1 = Money supply, and IND = Industrial production, and STP = Stock price.
In the second setting, the VAR model used by Christiano et al. (1998) is considered.[5] As they did, I use this model where T-bill/fund rate is used as a policy instrument and in addition I have included stock price.Therefore, T-bill/fund rate is used here to be influenced by contemporaneous events in industrial production and price indices. Thus,this identification scheme is very like the first benchmark identification scheme used by Christiano et al. (1998). The setup for this model is
=+ …++
Finally, for Indiaand US I have used GARCH(1,1)-AR(1) model to generate the conditional volatility series for all the variables. Then these volatility series are considered in a VAR framework. Sims’ identification scheme is used. This gives us the information about how T-bill/fund rate volatility innovations affect other macro variable- and stock price-volatility.
IV. Empirical Results
Figure 1 presents the impulse response function (IRF) from the similar model as used by Sims (1992). The only difference is that the data are extended to 2007:09 and a new variable, the log of stock price is included in the model.The IRF of this paper and that of Sims’ study are not that much different. Only the responses of all the variables with respect to the impulses to the Fed Fund Rate and stock price innovations are reported. The fund rateinnovation has impact on all other variables contemporaneously. Only the effect of exchange rate from fund rate shock is different. I find a negative impact on exchange rate that lasts from month 6 through month 48. It may happen so if Sims defines the exchange rate variable in a different way. He explains the positive effect as exchange rate appreciation. I calculate exchange rate as the US$ to SDR ratio.[6] Thus the decrease in the ratio means the appreciation in US$ and therefore the result is not different from Sims’. The result is also supported by theory since monetary policy contraction should raise the value of the domestic currency.
Figure1. Impulse Response Function for USA (1959:01 – 2007:09)
Shock 1 = Innovation in fund rate
Although not reported in the paper, interestingly like Sims I find a positive shock to money creates negative impact on industrial production. However, it is plausible that policy makers may feel the forthcoming inflationary pressure and take policy for contraction. Price may rise after contraction and the output may fall due to contraction of nominal demand and output.[7] The interest rate innovation causes stock price to go down. Obviously as interest rate has a positive innovation, the cost of capital or expected return goes up. Since the stock price is the present value of all the future cash flows (or dividends), stock price consequently goes down. It takes more than 30 months to absorb this shock.[8]
Identification as suggested by Christianno et. al. (1998) is used, but the results do not change much. Sims (1992) also admits that the innovations correlation are so low that different identification scheme under structural VAR framework do not give different results. This is probably a peculiarity when monthly data are used. Therefore, I am not reporting the results from the VAR identification of Christianno et al. (1998).
Figure 2 presents the responses of all the variables of Indiato one standard deviation innovation in T-bill (contemporaneously) and stock price (with one-month lag). Individual responses suggest weak relationship between monetary instrument and macroeconomic variables. The effect on output is mostly positive for the first 17 months and then it tends to be negative. This contrasts with the results for the US economy. Perhaps, Indian policy authority may have less visibility of forthcoming inflation. Moreover, the economies of developing countries are more segregated and autonomy of the central bank is relatively new. Innovations in T-bill causes negative response in stock price, which satisfies the notion that risk-free rate plays an important role in determining the risk-adjusted discount rate for calculating the stock price. The effect on exchange rate seems opposite of what is found for the USA. For India, the exchange rate is defined as Rupee/Dollar, which means positive response stands for appreciation in Rupee against dollar. Thus this result is also in line with the result of Sims.
Figure2. Impulse Response Function for India (1993:01 – 2006:12)
Shock 1 = Innovation in T-bill rate
The response of money supply is initially positive and then becomes negative after 6 months. For US, this response is much bigger compared to India. Moreover, it is negative since impact for US. Therefore, there is a kind of inertia in Indian economy for the response of money supply. Same thing happens for response of industrial production to interest rate innovation. For India, output take like 18 months to become negative whereas for US it takes about 8 months. Moreover, for India the response is smaller in magnitude.
Figure 3. Impulse Response Function for US (GARCH conditional st. dev.)